Interactive optimization techniques based on a column generation model for timetabling problems of university makeup courses

We focus on a timetabling problem of university makeup classes and construct a scheduling system based on man-machine interaction which enables to reveal the essential and additional information of the problem domain. In order to achieve operable timetables of the makeup classes it is required to consider the courses of every student in the university, because the makeup class timetable is made after the courses of each student were registered. Therefore, it is especially difficult to find feasible timetables. In this paper, we focus on the makeup class timetabling problem and develop the optimization system based on man-machine interaction using the column generation heuristics. In order to adopt the column generation heuristics, we show a set partitioning model of the target problem. Through some preliminary computational results, the effectiveness and the potential, e.g, for clarifying the effect of the column generation heuristics are investigated.